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"""
Input Node - Node đầu tiên để nhận tin nhắn từ người dùng với conversation cache
"""
import json
import logging
from pathlib import Path
from src.state.graph_state import TransportationState
from src.config.logging_config import get_logger
logger = get_logger(__name__)
class InputNode:
def __init__(self):
self.name = "input_node"
self.cache_file = Path(__file__).resolve().parents[3] / "conversation_cache.json"
def load_conversation_history(self) -> list:
"""Load conversation history từ cache file"""
try:
if self.cache_file.exists():
with open(self.cache_file, 'r', encoding='utf-8') as f:
conversations = json.load(f)
return conversations[-10:] # Last 10 conversations
return []
except Exception as e:
logger.error(f"Error loading conversation history: {e}")
return []
def get_context_from_history(self, conversations: list) -> str:
"""Generate context string từ conversation history với format role/content"""
if not conversations:
return ""
context = "Previous conversations for context:\n"
# Group messages by pairs (user, assistant)
messages = []
for i in range(0, len(conversations), 2):
if i + 1 < len(conversations):
user_msg = conversations[i]
assistant_msg = conversations[i + 1]
if user_msg.get('role') == 'user' and assistant_msg.get('role') == 'assistant':
messages.append((user_msg.get('content', ''), assistant_msg.get('content', '')))
# Show last 3 conversation pairs
for i, (user_content, assistant_content) in enumerate(messages[-3:], 1):
user_short = user_content[:50] + "..." if len(user_content) > 50 else user_content
assistant_short = assistant_content[:50] + "..." if len(assistant_content) > 50 else assistant_content
context += f"{i}. User: {user_short} → AI: {assistant_short}\n"
return context + "\nCurrent conversation:\n"
def process_input(self, state: TransportationState) -> TransportationState:
"""
Nhận tin nhắn từ state, load conversation history để có context
Args:
state: Current state với user_message
Returns:
Updated state với message và context
"""
user_message = state["user_message"]
logger.info(f"Received user message: {user_message[:100]}...")
try:
# Load conversation history
conversation_history = self.load_conversation_history()
state["conversation_cache"] = conversation_history
# Lưu message vào state (đã có sẵn)
state["user_message"] = user_message.strip()
state["current_step"] = "llm_processing"
state["error_message"] = None
# Add context cho LLM nếu có history
if conversation_history:
context = self.get_context_from_history(conversation_history)
state["user_message"] = context + user_message
logger.info(f"Added context from {len(conversation_history)} previous conversations")
logger.info("User message with context saved to state successfully")
except Exception as e:
error_msg = f"Error processing user input: {str(e)}"
logger.error(error_msg)
state["error_message"] = error_msg
return state
def __call__(self, state: TransportationState) -> TransportationState:
"""Callable interface cho LangGraph"""
return self.process_input(state)
# Factory function để tạo input node
def create_input_node() -> InputNode:
"""Tạo input node instance"""
return InputNode()
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